clip-02-05.jl
Load Julia packages (libraries) needed for the snippets in chapter 0
using StatisticalRethinking, Optim
gr(size=(600,300));Plots.GRBackend()snippet 3.2
p_grid = range(0, step=0.001, stop=1)
prior = ones(length(p_grid))
likelihood = [pdf(Binomial(9, p), 6) for p in p_grid]
posterior = likelihood .* prior
posterior = posterior / sum(posterior)
samples = sample(p_grid, Weights(posterior), length(p_grid));
samples[1:5]5-element Array{Float64,1}:
0.6
0.613
0.388
0.691
0.548snippet 3.3
Draw 10000 samples from this posterior distribution
N = 10000
samples = sample(p_grid, Weights(posterior), N);10000-element Array{Float64,1}:
0.565
0.671
0.591
0.746
0.736
0.602
0.728
0.753
0.741
0.53
⋮
0.403
0.744
0.373
0.573
0.626
0.57
0.732
0.47
0.662In StatisticalRethinkingJulia samples will always be stored in an MCMCChains.Chains object.
chn = MCMCChains.Chains(reshape(samples, N, 1, 1), ["toss"]);Object of type Chains, with data of type 10000×1×1 Array{Float64,3}
Iterations = 1:10000
Thinning interval = 1
Chains = 1
Samples per chain = 10000
parameters = toss
parameters
Mean SD Naive SE MCSE ESS
toss 0.6366 0.1395 0.0014 0.0015 8606.187
Describe the chain
describe(chn)Iterations = 1:10000
Thinning interval = 1
Chains = 1
Samples per chain = 10000
parameters = toss
Empirical Posterior Estimates
───────────────────────────────────────────
parameters
Mean SD Naive SE MCSE ESS
toss 0.6366 0.1395 0.0014 0.0015 8606.187
Quantiles
───────────────────────────────────────────
parameters
2.5% 25.0% 50.0% 75.0% 97.5%
toss 0.347 0.543 0.646 0.741 0.877Plot the chain
plot(chn)
snippet 3.4
Create a vector to hold the plots so we can later combine them
p = Vector{Plots.Plot{Plots.GRBackend}}(undef, 2)
p[1] = scatter(1:N, samples, markersize = 2, ylim=(0.0, 1.3), lab="Draws")
snippet 3.5
Analytical calculation
w = 6
n = 9
x = 0:0.01:1
p[2] = density(samples, ylim=(0.0, 5.0), lab="Sample density")
p[2] = plot!( x, pdf.(Beta( w+1 , n-w+1 ) , x ), lab="Conjugate solution")
Add quadratic approximation
plot(p..., layout=(1, 2))
End of 03/clip-02-05.jl
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